Bibliographic record
Abstract
This study explores the role of justice in eleven historical cases of inter-governmental negotiation. Building on results obtained in several recent studies on justice in negotiation, we examine a set of hypotheses about relationships among negotiating process (as distributive bargaining or problem solving), justice (as procedural and distributive), outcomes (as compromise or integrative), and the duration of the agreements. The process variables were coded from negotiators’ statements with categories from the bargaining process analysis system. The justice variables were coded with a system developed in recent studies on peace agreements. Similar to results obtained by Hollander-Blumoff and Tyler (2008) in a simulated legal setting, we find correlations between procedural justice, problem solving and integrative outcomes. Similar to results obtained by Druckman and Albin (2011) on peace agreements, we find a strong relationship between distributive justice and the durability of the agreement. In these cases, problem-solving processes were shown to mediate the relationship between procedural justice and integrative outcomes. The findings suggest that justice plays an important role across a variety of negotiation settings. We present these results as heuristic, suggesting avenues for further research on larger and more diverse samples of cases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.020 | 0.028 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".